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Building ​intelligent applications in a smart city is one of the largest challenges we can face in modern times. Problems in smart cities are varied (according to EU: economy, mobility, governance, people, living, environment), multidisciplinary in nature, ​apparently unrelated ​, and require a vast ​scientific luggage to face them. Instead of going for core methodologies or knowledge building, most current works just deal with the final application, neglecting the ​research ​part of this domain. Present services are proposed with no fundamental methodology, just as separate ideas for different parts of the city, thus creating silos ​of expertise that prevent an appropriate long term development. One of the many missed opportunities is to research in the ​similarities between different problems to profit from existing knowledge in these separate domains and make cross-domain proposals.

Our ​hypothesis ​of work in this project is that we can solve many different problems in the mentioned domains by looking at their (possibly similar) underlying quantitative and qualitative features, as well as by providing ​advanced algorithms ​that can ​search, optimize and learn ​by themselves (to an extent) for those situations where knowledge of the problem is very limited (as it happens in many real cases). This "​cross-intelligence" will go from pure philosophy to precise mathematical operations: found in one field but used in another one. The expression in the universal language of ​maths ​of the problems will be one of the bases for a later inspiration in other scientific (sub)domains.

One of the clear guides for development in smart cities are the fields to work on. In fact, ​Spain and Europe have many similarities in their plans for smart cities. In particular, they define ​six axes of work. In this project, we will identify, solve and make prototypes of applications and services in all the six axes (hence ​6city​):

Our jump and ambition are high: our previous project just dealt with ​mobility​, while this proposal goes for all axes; in fact, all the proposed services can be classified in many axes at the same time. Since this proposal is very ​practical ​, we will provide Android apps, web services and technical deliverables, even looking for in-project ​industrial transference to companies.

This ​cross-intelligence approach will consider hardware, software, maths and domain knowledge exchanges in a methodological way. We use existing information (open data), present data (sensors) and predictions in our applications (holistic in time​), as well as we act at streets, home, roads and the city itself (holistic in space). The challenges are many and hard, so we will ​extend state of the art techniques ​in optimization, machine learning, and data analytics for providing usable applications and a long lasting base research on algorithms, their fundamentals and new ways of adapting them to city platforms (like smartphones and cyber-physical systems). This ​science+industry approach will hopefully have a considerable impact.